Accurate and efficient prediction of acoustical performance of noise barriers against transport noise pollution

Peng, S.Z., and Sun, H.M. (2009) Accurate and efficient prediction of acoustical performance of noise barriers against transport noise pollution. International Journal of Vehicle Noise and Vibration, 5 (1-2). pp. 53-90.

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Abstract

An improved acoustical wave propagator (I_AWP) technique with high-order absorbing boundary technique is introduced to evaluate the acoustical wave interaction for noise barriers, providing the dual benefit of preserving high numerical accuracy (boundary conditions have been properly treated) and obtaining high computational efficiency (using a larger time step in the calculation). The aim is to establish a framework for effective design of noise barriers based on (a) in the time-domain, the evolution of wave propagation and analyses of acoustical-structure interaction, then a good understanding of time-domain acoustical wave diffraction (one key noise abatement mechanism) can be achieved, and (b) in the frequency-domain, the effects of noise barriers with different structures and noise sources at different locations on sound pressure distribution, especially noise barriers with a simple smart structure (membranes) are investigated in detail. These investigations produce a database for effective and optimal design of noise barriers. More importantly, the outcome can provide a deep insight to the acoustical performance of noise barriers in reducing noise pollution in urban environments and other applications.

Item ID: 11280
Item Type: Article (Research - C1)
ISSN: 1479-148X
Keywords: acoustic wave propagation; acoustic-structure interaction; noise barriers; transport noise; noise pollution; vehicle noise; noise barrier design; acoustic performance
Date Deposited: 03 Jun 2010 01:18
FoR Codes: 09 ENGINEERING > 0913 Mechanical Engineering > 091301 Acoustics and Noise Control (excl Architectural Acoustics) @ 100%
SEO Codes: 86 MANUFACTURING > 8614 Machinery and Equipment > 861403 Industrial Machinery and Equipment @ 100%
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